Results 161 to 170 of about 1,895,251 (293)

microRNA‐7‐5p and α‐Synuclein SAA Predict Parkinson's Disease Phenoconversion

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Corroborate blood neuron‐derived extracellular vesicle (NDEV) alpha‐synuclein (αSyn), the CSF αSyn seed amplification assay (αSyn‐SAA), and blood microRNA‐7‐5p (miR‐7‐5p) as markers for Parkinson's disease (PD) phenoconversion and determine if combining these markers would help select subjects who would be more likely to phenoconvert.
Shayan Zadegan   +4 more
wiley   +1 more source

Glucagon‐Like Peptide‐1 Receptor Agonists in Multiple Sclerosis: A Topical Narrative Review

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT The glucagon‐like peptide‐1 (GLP‐1) receptor agonists (RAs) are a relatively new class of drugs that were initially approved by the US Food and Drug Administration to improve glycemic control in patients with type 2 diabetes mellitus and, subsequently, weight reduction in patients with obesity.
Audrey Y. Chang, Farrah J. Mateen
wiley   +1 more source

Dynamic Changes in Serum Glial Fibrillary Acidic Protein Levels Predicts Early Neurological Deterioration After Intravenous Thrombolysis in Minor Stroke

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Minor strokes may be associated with early neurological deterioration (END) and disabilities. The objective was to investigate the role of serum glial fibrillary acidic protein (GFAP) levels in predicting END. Methods Data originated from a multicenter cohort study conducted prospectively.
Jie Zhou   +45 more
wiley   +1 more source

Stage‐Specific Patterns of Imaging and Non‐Motor Biomarkers in Spinocerebellar Ataxia Type 3

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Advancements in disease‐modifying therapies for spinocerebellar ataxia Type 3 (SCA3) underscore the need for robust biomarkers to monitor disease progression and evaluate treatment efficacy. Although motor phenotypes have been well characterized, less is known about non‐motor and imaging‐based features across different disease stages.
Chun Li   +17 more
wiley   +1 more source

Parkinson Disease Subtype Stability and Eventual Convergence

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Previous research identified distinct Parkinson disease (PD) clinical subtypes of “Motor Only,” “Psychiatric & Motor,” and “Cognitive & Motor” based on comprehensive, multidomain classification. Whether these subtypes reflect distinct trajectories or progressive disease stages remains unknown.
Laura M. Rosok   +10 more
wiley   +1 more source

Clinician and Patient Factors Associated With Long‐Term Glucocorticoid Use in People With Rheumatoid Arthritis Receiving Advanced Therapies

open access: yesArthritis Care &Research, EarlyView.
Objective Despite guideline recommendations, long‐term glucocorticoid (GC) use is common in rheumatoid arthritis (RA). We conducted a clinician survey nested within a large registry to identify patient and clinician factors associated with GC use. Methods Clinicians contributing patients to the CorEvitas Rheumatoid Arthritis Registry were surveyed ...
Michael D. George   +7 more
wiley   +1 more source

Short‐Term Response to Biologic Therapy in Psoriatic Arthritis Is Not Influenced by Disease Duration at Initiation of Therapy

open access: yesArthritis Care &Research, EarlyView.
Objective We aimed to determine whether the short‐term response to biologics in biologic‐naive psoriatic arthritis (PsA) is better in patients initiating biologic treatment early in the disease course. Methods Patients with PsA who started on biologic therapy from the year 2000 to 2025 were included for analysis.
Sung Min Cho   +4 more
wiley   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli   +3 more
wiley   +1 more source

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